通过排列两个变量来添加计数器列(dplyr)

时间:2017-07-11 22:02:57

标签: r count group-by dplyr

我一直在寻找一段时间,但我无法找到解决方案。我有一个数据框,其中包含ID和VAR。我在下面试图复制一个样本

require(dplyr)
seed(123)
N <- 3
T <- 4
id <- rep(letters[1:N], each = T) 
var <- rep(sample(seq(1:100),T),N) 
row <- sample(seq(1:(N*T)),replace = F)

dt <- data.frame(ID=id,VAR=var,ROW=row) %>%
  arrange(ROW) %>%
  select(-ROW)

我想通过ID和VAR arrange并为每个组添加一个计数器以获得类似

的内容
   ID VAR COUNTER
1   a   1 1
2   a  11 2
3   a  22 3
4   a  64 4
5   b   1 1
6   b  11 2
7   b  22 3
8   b  64 4
9   c   1 1
10  c  11 2
11  c  22 3
12  c  64 4

所有这些,如果可能的话,只需使用dplyr或基本函数。

1 个答案:

答案 0 :(得分:5)

dplyr内,您需要arrange() IDVAR以及group_by() ID {/ 1}}。{/ p>

然后使用mutate()添加新列,从1到n()计数(其中n()是'行数'的dplyr函数)

set.seed(123)
dt %>%
    arrange(ID, VAR) %>%
    group_by(ID) %>%
    mutate(COUNTER = 1:n()) %>%  ## as per comment, can use row_number()
    ungroup()

# # A tibble: 12 × 3
#         ID   VAR COUNTER
#     <fctr> <int>   <int>
# 1       a    29       1
# 2       a    41       2
# 3       a    79       3
# 4       a    86       4
# 5       b    29       1
# 6       b    41       2
# 7       b    79       3
# 8       b    86       4
# 9       c    29       1
# 10      c    41       2
# 11      c    79       3
# 12      c    86       4

关于取消分组的评论

我这样做是为了删除与grouped_df相关联的所有“分组”属性。在这个例子中,结果是相同的,但那些分组的属性可能会让你更进一步。

dt_grouped <- dt %>%
    arrange(ID, VAR) %>%
    group_by(ID) %>%
    mutate(COUNTER = 1:n()) 

dt_ungrouped <- dt %>%
    arrange(ID, VAR) %>%
    group_by(ID) %>%
    mutate(COUNTER = 1:n()) %>%
    ungroup()

str(dt_grouped)
# Classes ‘grouped_df’, ‘tbl_df’, ‘tbl’ and 'data.frame':   12 obs. of  3 variables:
#   $ ID     : Factor w/ 3 levels "a","b","c": 1 1 1 1 2 2 2 2 3 3 ...
# $ VAR    : int  29 41 79 86 29 41 79 86 29 41 ...
# $ COUNTER: int  1 2 3 4 1 2 3 4 1 2 ...
# - attr(*, "vars")=List of 1
# ..$ : symbol ID
# - attr(*, "labels")='data.frame': 3 obs. of  1 variable:
#   ..$ ID: Factor w/ 3 levels "a","b","c": 1 2 3
# ..- attr(*, "vars")=List of 1
# .. ..$ : symbol ID
# ..- attr(*, "drop")= logi TRUE
# - attr(*, "indices")=List of 3
# ..$ : int  0 1 2 3
# ..$ : int  4 5 6 7
# ..$ : int  8 9 10 11
# - attr(*, "drop")= logi TRUE
# - attr(*, "group_sizes")= int  4 4 4
# - attr(*, "biggest_group_size")= int 4

str(dt_ungrouped)
# Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 12 obs. of  3 variables:
#   $ ID     : Factor w/ 3 levels "a","b","c": 1 1 1 1 2 2 2 2 3 3 ...
# $ VAR    : int  29 41 79 86 29 41 79 86 29 41 ...
# $ COUNTER: int  1 2 3 4 1 2 3 4 1 2 ...